Obtaining high-resolution velocity spectra using weighted semblance
Saleh Ebrahimi 1 Amin Roshandel Kahoo 1 3 Milton J. Porsani 2 Ali Nejati Kalateh 11 School of Mining, Petroleum and Geophysics Engineering, University of Shahrood, PO Box 3619995161, Semnan, Shahrood, Iran.
2 Centro de Pesquisa em Geofísica e Geologia (CPPG/UFBA) and National Institute of Science and Technology of Petroleum Geophysics (INCT-GP/CNPQ), Instituto de Geociências, Universidade Federal da Bahia Campus Universitário da Federacão, Salvador, Bahia, Brazil.
3 Corresponding author. Email: roshandel@shahroodut.ac.ir
Exploration Geophysics 48(3) 210-218 https://doi.org/10.1071/EG15100
Submitted: 25 September 2015 Accepted: 12 January 2016 Published: 5 February 2016
Abstract
Velocity analysis employs coherency measurement along a hyperbolic or non-hyperbolic trajectory time window to build velocity spectra. Accuracy and resolution are strictly related to the method of coherency measurements. Semblance, the most common coherence measure, has poor resolution velocity which affects one’s ability to distinguish and pick distinct peaks. Increase the resolution of the semblance velocity spectra causes the accuracy of estimated velocity for normal moveout correction and stacking is improved. The low resolution of semblance spectra depends on its low sensitivity to velocity changes.
In this paper, we present a new weighted semblance method that ensures high-resolution velocity spectra. To increase the resolution of semblance spectra, we introduce two weighting functions based on the first to second singular values ratio of the time window and the position of the seismic wavelet in the time window to the semblance equation. We test the method on both synthetic and real field data to compare the resolution of weighted and conventional semblance methods. Numerical examples with synthetic and real seismic data indicate that the new proposed weighted semblance method provides higher resolution than conventional semblance and can separate the reflectors which are mixed in the semblance spectrum.
Key words: seismic, semblance, singular value decomposition, velocity analysis.
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